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@@ -0,0 +1 @@ +/cca_zoo-1.17.7.tar.gz diff --git a/python-cca-zoo.spec b/python-cca-zoo.spec new file mode 100644 index 0000000..de19a71 --- /dev/null +++ b/python-cca-zoo.spec @@ -0,0 +1,415 @@ +%global _empty_manifest_terminate_build 0 +Name: python-cca-zoo +Version: 1.17.7 +Release: 1 +Summary: Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework +License: MIT +URL: https://github.com/jameschapman19/cca_zoo +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/79/58/d137e5dfc61e77e2abf5d1211d5b30bbaa82635adc44fe58312498342ca2/cca_zoo-1.17.7.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-scikit-learn +Requires: python3-scikit-prox +Requires: python3-pytest +Requires: python3-matplotlib +Requires: python3-pandas +Requires: python3-seaborn +Requires: python3-tensorly +Requires: python3-joblib +Requires: python3-mvlearn +Requires: python3-tqdm +Requires: python3-setuptools +Requires: python3-torch +Requires: python3-torchvision +Requires: python3-pytorch-lightning +Requires: python3-jax +Requires: python3-numpyro +Requires: python3-arviz +Requires: python3-torch +Requires: python3-torchvision +Requires: python3-pytorch-lightning +Requires: python3-jax +Requires: python3-numpyro +Requires: python3-arviz + +%description +[](https://doi.org/10.5281/zenodo.4382739) +[](https://codecov.io/gh/jameschapman19/cca_zoo) + +[](https://cca-zoo.readthedocs.io/en/latest/?badge=latest) +[](https://pypi.org/project/cca-zoo/) +[](https://pypi.org/project/cca-zoo/) +[](https://doi.org/10.21105/joss.03823) + +# CCA-Zoo + +`cca-zoo` is a collection of linear, kernel, and deep methods for canonical correlation analysis of multiview data. +Where possible it follows the `scikit-learn`/`mvlearn` APIs and models therefore have `fit`/`transform`/`fit_transform` +methods as standard. + +## Installation + +Dependency of some implemented algorithms are heavy, such as `pytorch` and `numpyro`. +We provide several options to accomodate the user's needs. +For full details of algorithms included, please refer to section [Implemented Methods](#implemented-methods) + +Standard installation: + +``` +pip install cca-zoo +``` + +For deep learning elements use: + +``` +pip install cca-zoo[deep] +``` + +For probabilistic elements use: + +``` +pip install cca-zoo[probabilistic] +``` + +## Documentation + +Available at https://cca-zoo.readthedocs.io/en/latest/ + +## Citation: + +CCA-Zoo is intended as research software. Citations and use of our software help us justify the effort which has gone +into, and will keep going into, maintaining and growing this project. Stars on the repo are also greatly appreciated :) + +If you have used CCA-Zoo in your research, please consider citing our JOSS paper: + +Chapman et al., (2021). CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods +in a scikit-learn style framework. Journal of Open Source Software, 6(68), 3823, https://doi.org/10.21105/joss.03823 + +With bibtex entry: + +```bibtex +@article{Chapman2021, + doi = {10.21105/joss.03823}, + url = {https://doi.org/10.21105/joss.03823}, + year = {2021}, + publisher = {The Open Journal}, + volume = {6}, + number = {68}, + pages = {3823}, + author = {James Chapman and Hao-Ting Wang}, + title = {CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods in a scikit-learn style framework}, + journal = {Journal of Open Source Software} +} +``` + +## Contributions + +A guide to contributions is available at https://cca-zoo.readthedocs.io/en/latest/developer_info/contribute.html + +## Sources + +I've added this section to give due credit to the repositories that helped me in addition to their copyright notices in +the code where relevant. + +### Other Implementations of (regularised)CCA/PLS + +[MATLAB implementation](https://github.com/anaston/PLS_CCA_framework) + +### Implementation of Sparse PLS + +MATLAB implementation of SPLS by [@jmmonteiro](https://github.com/jmmonteiro/spls) + +### Other Implementations of DCCA/DCCAE + +Keras implementation of DCCA from [@VahidooX's github page](https://github.com/VahidooX) + +The following are the other implementations of DCCA in MATLAB and C++. These codes are written by the authors of the +original paper: + +[Torch implementation](https://github.com/Michaelvll/DeepCCA) of DCCA from @MichaelVll & @Arminarj + +C++ implementation of DCCA from Galen Andrew's [website](https://homes.cs.washington.edu/~galen/) + +MATLAB implementation of DCCA/DCCAE from Weiran Wang's [website](http://ttic.uchicago.edu/~wwang5/dccae.html) + +MATLAB implementation of [TCCA](https://github.com/rciszek/mdr_tcca) + +### Implementation of VAE + +[Torch implementation of VAE](https://github.com/pytorch/examples/tree/master/vae) + + + + +%package -n python3-cca-zoo +Summary: Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework +Provides: python-cca-zoo +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-cca-zoo +[](https://doi.org/10.5281/zenodo.4382739) +[](https://codecov.io/gh/jameschapman19/cca_zoo) + +[](https://cca-zoo.readthedocs.io/en/latest/?badge=latest) +[](https://pypi.org/project/cca-zoo/) +[](https://pypi.org/project/cca-zoo/) +[](https://doi.org/10.21105/joss.03823) + +# CCA-Zoo + +`cca-zoo` is a collection of linear, kernel, and deep methods for canonical correlation analysis of multiview data. +Where possible it follows the `scikit-learn`/`mvlearn` APIs and models therefore have `fit`/`transform`/`fit_transform` +methods as standard. + +## Installation + +Dependency of some implemented algorithms are heavy, such as `pytorch` and `numpyro`. +We provide several options to accomodate the user's needs. +For full details of algorithms included, please refer to section [Implemented Methods](#implemented-methods) + +Standard installation: + +``` +pip install cca-zoo +``` + +For deep learning elements use: + +``` +pip install cca-zoo[deep] +``` + +For probabilistic elements use: + +``` +pip install cca-zoo[probabilistic] +``` + +## Documentation + +Available at https://cca-zoo.readthedocs.io/en/latest/ + +## Citation: + +CCA-Zoo is intended as research software. Citations and use of our software help us justify the effort which has gone +into, and will keep going into, maintaining and growing this project. Stars on the repo are also greatly appreciated :) + +If you have used CCA-Zoo in your research, please consider citing our JOSS paper: + +Chapman et al., (2021). CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods +in a scikit-learn style framework. Journal of Open Source Software, 6(68), 3823, https://doi.org/10.21105/joss.03823 + +With bibtex entry: + +```bibtex +@article{Chapman2021, + doi = {10.21105/joss.03823}, + url = {https://doi.org/10.21105/joss.03823}, + year = {2021}, + publisher = {The Open Journal}, + volume = {6}, + number = {68}, + pages = {3823}, + author = {James Chapman and Hao-Ting Wang}, + title = {CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods in a scikit-learn style framework}, + journal = {Journal of Open Source Software} +} +``` + +## Contributions + +A guide to contributions is available at https://cca-zoo.readthedocs.io/en/latest/developer_info/contribute.html + +## Sources + +I've added this section to give due credit to the repositories that helped me in addition to their copyright notices in +the code where relevant. + +### Other Implementations of (regularised)CCA/PLS + +[MATLAB implementation](https://github.com/anaston/PLS_CCA_framework) + +### Implementation of Sparse PLS + +MATLAB implementation of SPLS by [@jmmonteiro](https://github.com/jmmonteiro/spls) + +### Other Implementations of DCCA/DCCAE + +Keras implementation of DCCA from [@VahidooX's github page](https://github.com/VahidooX) + +The following are the other implementations of DCCA in MATLAB and C++. These codes are written by the authors of the +original paper: + +[Torch implementation](https://github.com/Michaelvll/DeepCCA) of DCCA from @MichaelVll & @Arminarj + +C++ implementation of DCCA from Galen Andrew's [website](https://homes.cs.washington.edu/~galen/) + +MATLAB implementation of DCCA/DCCAE from Weiran Wang's [website](http://ttic.uchicago.edu/~wwang5/dccae.html) + +MATLAB implementation of [TCCA](https://github.com/rciszek/mdr_tcca) + +### Implementation of VAE + +[Torch implementation of VAE](https://github.com/pytorch/examples/tree/master/vae) + + + + +%package help +Summary: Development documents and examples for cca-zoo +Provides: python3-cca-zoo-doc +%description help +[](https://doi.org/10.5281/zenodo.4382739) +[](https://codecov.io/gh/jameschapman19/cca_zoo) + +[](https://cca-zoo.readthedocs.io/en/latest/?badge=latest) +[](https://pypi.org/project/cca-zoo/) +[](https://pypi.org/project/cca-zoo/) +[](https://doi.org/10.21105/joss.03823) + +# CCA-Zoo + +`cca-zoo` is a collection of linear, kernel, and deep methods for canonical correlation analysis of multiview data. +Where possible it follows the `scikit-learn`/`mvlearn` APIs and models therefore have `fit`/`transform`/`fit_transform` +methods as standard. + +## Installation + +Dependency of some implemented algorithms are heavy, such as `pytorch` and `numpyro`. +We provide several options to accomodate the user's needs. +For full details of algorithms included, please refer to section [Implemented Methods](#implemented-methods) + +Standard installation: + +``` +pip install cca-zoo +``` + +For deep learning elements use: + +``` +pip install cca-zoo[deep] +``` + +For probabilistic elements use: + +``` +pip install cca-zoo[probabilistic] +``` + +## Documentation + +Available at https://cca-zoo.readthedocs.io/en/latest/ + +## Citation: + +CCA-Zoo is intended as research software. Citations and use of our software help us justify the effort which has gone +into, and will keep going into, maintaining and growing this project. Stars on the repo are also greatly appreciated :) + +If you have used CCA-Zoo in your research, please consider citing our JOSS paper: + +Chapman et al., (2021). CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods +in a scikit-learn style framework. Journal of Open Source Software, 6(68), 3823, https://doi.org/10.21105/joss.03823 + +With bibtex entry: + +```bibtex +@article{Chapman2021, + doi = {10.21105/joss.03823}, + url = {https://doi.org/10.21105/joss.03823}, + year = {2021}, + publisher = {The Open Journal}, + volume = {6}, + number = {68}, + pages = {3823}, + author = {James Chapman and Hao-Ting Wang}, + title = {CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods in a scikit-learn style framework}, + journal = {Journal of Open Source Software} +} +``` + +## Contributions + +A guide to contributions is available at https://cca-zoo.readthedocs.io/en/latest/developer_info/contribute.html + +## Sources + +I've added this section to give due credit to the repositories that helped me in addition to their copyright notices in +the code where relevant. + +### Other Implementations of (regularised)CCA/PLS + +[MATLAB implementation](https://github.com/anaston/PLS_CCA_framework) + +### Implementation of Sparse PLS + +MATLAB implementation of SPLS by [@jmmonteiro](https://github.com/jmmonteiro/spls) + +### Other Implementations of DCCA/DCCAE + +Keras implementation of DCCA from [@VahidooX's github page](https://github.com/VahidooX) + +The following are the other implementations of DCCA in MATLAB and C++. These codes are written by the authors of the +original paper: + +[Torch implementation](https://github.com/Michaelvll/DeepCCA) of DCCA from @MichaelVll & @Arminarj + +C++ implementation of DCCA from Galen Andrew's [website](https://homes.cs.washington.edu/~galen/) + +MATLAB implementation of DCCA/DCCAE from Weiran Wang's [website](http://ttic.uchicago.edu/~wwang5/dccae.html) + +MATLAB implementation of [TCCA](https://github.com/rciszek/mdr_tcca) + +### Implementation of VAE + +[Torch implementation of VAE](https://github.com/pytorch/examples/tree/master/vae) + + + + +%prep +%autosetup -n cca-zoo-1.17.7 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-cca-zoo -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.17.7-1 +- Package Spec generated @@ -0,0 +1 @@ +b3daa78f56c13b667e8e0aa52f10311c cca_zoo-1.17.7.tar.gz |